ArticleScientific reports2011
Unified regression model of binding equilibria in crowded environments.
Article in Scientific reports, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed.
- Deathdaily: A Python Package Index for predicting the number of daily COVID-19 deaths.Network modeling and analysis in health informatics and bioinformatics · 2022Article
- Mechanical, nanomorphological and biological reconstruction of early‑stage apoptosis in HeLa cells induced by cytochalasin B.Oncology reports · 2019Article
- Reaching new levels of realism in modeling biological macromolecules in cellular environments.Journal of molecular graphics & modelling · 2013Review
- Looking for a promoter in 3D.Nature structural & molecular biology · 2013Article
- Three-dimensional stochastic off-lattice model of binding chemistry in crowded environments.PloS one · 2012Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Molecular crowding is a critical feature distinguishing intracellular environments from idealized solution-based environments and is essential to understanding numerous biochemical reactions, from protein folding to signal transduction. Many biochemical reactions are dramatically altered by crowding, yet it is extremely difficult to predict how crowding will quantitatively affect any particular reaction systems. We previously developed a novel stochastic off-lattice model to efficiently simulate binding reactions across wide parameter ranges in various crowded conditions. We now show that a polynomial regression model can incorporate several interrelated parameters influencing chemistry under crowded conditions. The unified model of binding equilibria accurately reproduces the results of particle simulations over a broad range of variation of six physical parameters that collectively yield a complicated, non-linear crowding effect. The work represents an important step toward the long-term goal of computationally tractable predictive models of reaction chemistry in the cellular environment.
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Registered trials
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